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Learning Interpretable Queries for Explainable Image Classification with Information Pursuit

Information Pursuit (IP) is an explainable prediction algorithm that greedily selects a sequence of interpretable queries about the data in order of information gain, updating its posterior at each step based on observed query-answer pairs.

Data and Resources

Cite this as

Stefan Kolek, Aditya Chattopadhyay, Kwan Ho Ryan Chan, Hector Andrade-Loarca, Gitta Kutyniok, Ren´e Vidal (2024). Dataset: Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. https://doi.org/10.57702/4m38jdk3

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2312.11548
Author Stefan Kolek
More Authors
Aditya Chattopadhyay
Kwan Ho Ryan Chan
Hector Andrade-Loarca
Gitta Kutyniok
Ren´e Vidal